Skip to content

Instantly share code, notes, and snippets.

Show Gist options
  • Save mesmesgit/4152556a749083531c9c18245dbf5930 to your computer and use it in GitHub Desktop.
Save mesmesgit/4152556a749083531c9c18245dbf5930 to your computer and use it in GitHub Desktop.
CUDA 10.2 Installation on Ubuntu 18.04
#!/bin/bash
## This gist contains instructions about cuda v10.2 and cudnn 7.6 installation in Ubuntu 18.04 for Tensorflow 2.1.0
# Rev MES 9/5/20 - hopefully this will work for opencv build as well
### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###
### If you have previous installation remove it first.
sudo apt-get purge nvidia*
sudo apt remove nvidia-*
sudo rm /etc/apt/sources.list.d/cuda*
sudo apt-get autoremove && sudo apt-get autoclean
sudo rm -rf /usr/local/cuda*
sudo apt-get purge cuda
sudo apt-get autoremove --purge cuda*
# Use sudo dpkg -r to remove cuda-*
# Use sudo dpkg -P to purge all the cuda deb packages individually. These deb packages were listed by dpkg -l | grep cuda
# use sudo dpkg -l | grep nvidia to find packages and remove with sudo dpkg -P
# use sudo dpkg -l | grep cuda to find packages and remove with sudo dpkg -P
sudo apt-get remove --purge '^nvidia-.*'
sudo apt-get --purge remove libnvidia-compute-440
### to verify your gpu is cuda enable check
lspci | grep -i nvidia
### gcc compiler is required for development using the cuda toolkit. to verify the version of gcc install enter
gcc --version
# system update
sudo apt-get update
sudo apt-get upgrade
# install other import packages
sudo apt-get install g++ freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev
# first get the PPA repository driver
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 /" | sudo tee /etc/apt/sources.list.d/cuda.list
sudo apt-get update
# installing CUDA-10.2
sudo apt-get -o Dpkg::Options::="--force-overwrite" install cuda-10-2 cuda-drivers
# download 10.2 cuBLAS patch1, dated 8/26/2020 from:
# https://developer.nvidia.com/cuda-10.2-download-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1804&target_type=runfilelocal
# follow instructions to install local runfile using sh
# setup your paths
echo 'export PATH=/usr/local/cuda-10.2/bin:$PATH' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=/usr/local/cuda-10.2/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc
source ~/.bashrc
sudo ldconfig
# install cuDNN v7.6
# in order to download cuDNN you have to be regeistered here https://developer.nvidia.com/developer-program/signup
# then download cuDNN v7.6 form https://developer.nvidia.com/cudnn
CUDNN_TAR_FILE="cudnn-10.2-linux-x64-v7.6.5.32.tgz"
# download cudnn above, but URL below is incorrect
# wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/7.6.5.32/Production/10.1_20191031/cudnn-10.2-linux-x64-v7.6.5.32.tgz
tar -xzvf ${CUDNN_TAR_FILE}
# copy the following files into the cuda toolkit directory.
sudo cp -P cuda/include/cudnn.h /usr/local/cuda-10.2/include
sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda-10.2/lib64/
sudo chmod a+r /usr/local/cuda-10.2/lib64/libcudnn*
# Finally, to verify the installation, check
nvidia-smi
nvcc -V
# install Tensorflow (an open source machine learning framework)
# I choose version 2.1.0 because it is stable and compatible with CUDA 10.1 Toolkit and cuDNN 7.6
sudo pip3 install --user tensorflow-gpu==2.1.0
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment